Senior Data Engineer
Summary
Design, build, and maintain enterprise-scale big data platforms and pipelines at HCLTech in Kuala Lumpur, using Python, Apache Spark/PySpark, SQL, Airflow, and Kubernetes on Linux, with DevOps practices like CI/CD, automation, and performance tuning.
Job Description: Big Data Platform Engineer
Role Summary
We are seeking a highly motivated and skilled Big Data Platform Engineer to design, develop, and maintain scalable data processing platforms and pipelines. The ideal candidate should have strong expertise in Python, Apache Spark, SQL, and experience working in Linux-based environments with exposure to DevOps practices. The role involves building reliable, high-performance data solutions that support enterprise-scale analytics and business-critical applications.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Python and Apache Spark.
- Implement efficient ETL/ELT processes for large-scale structured and unstructured datasets.
- Develop and optimize complex SQL queries, data models, and transformations.
- Ensure data quality, integrity, and reliability across the platform.
Platform Operations
- Work with Linux-based environments for deployment, troubleshooting, and performance tuning.
- Develop and maintain shell scripts for automation and operational tasks.
- Monitor and optimize Spark jobs for performance, scalability, and resource utilization.
DevOps & Automation
- Implement CI/CD pipelines and deployment automation.
- Participate in infrastructure provisioning, monitoring, and release management activities.
- Collaborate with DevOps teams to improve platform reliability and operational efficiency.
- Work closely with Data Architects, Product Owners, and Business Stakeholders.
- Participate in code reviews and ensure adherence to engineering best practices.
- Create and maintain technical documentation and operational runbooks.
Mandatory Skills
Core Big Data Platform Skills
- Strong programming experience in Python
- Hands-on expertise with Apache Spark (PySpark preferred)
- Strong SQL development and query optimization skills
- Apache Airflow for workflow orchestration and scheduling
- Kubernetes (AKS/SKE) for container orchestration and deployment
- MinIO / S3 Compatible Object Storage
- ETL/ELT Processing
- Performance Tuning
- Version Control (Git)
- Agile/Scrum Delivery Model
Good to Have Skills
- Shell Scripting (Bash/KSH)
- Understanding of DevOps practices and CI/CD pipelines
- Docker and Containerization Concepts
- Cloud Platform Experience (Azure/AWS)
Desired Experience
- 6 to 8 years of experience or 8 to 12 years or 12+ years of experience in Data Engineering or Big Data Platform Development.
- Experience working with enterprise-scale data platforms.
- Experience in distributed computing environments.
Strong analytical and problem-solving skills.